• Title/Summary/Keyword: Gradient operator

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Performance Analysis of Adaptive Corner Shrinking Algorithm for Decimating the Document Image (문서 영상 축소를 위한 적응형 코너 축소 알고리즘의 성능 분석)

  • Kwak No-Yoon
    • Journal of Digital Contents Society
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    • v.4 no.2
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    • pp.211-221
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    • 2003
  • The objective of this paper is performance analysis of the digital document image decimation algorithm which generates a value of decimated element by an average of a target pixel value and a value of neighbor intelligible element to adaptively reflect the merits of ZOD method and FOD method on the decimated image. First, a target pixel located at the center of sliding window is selected, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each local intelligible weight. Next, a value of neighbor intelligible element is obtained by adding a value of the right neighbor pixel times its local intelligible weight to a value of the lower neighbor pixel times its intelligible weight. The decimated image can be acquired by applying the process repetitively to all pixels in input image which generates the value of decimated element by calculating the average of the target pixel value and the value of neighbor intelligible element. In this paper, the performance comparison of proposed method and conventional methods in terms of subjective performance and hardware complexity is analyzed and the preferable approach for developing the decimation algorithm of the digital document image on the basis of this analysis result has been reviewed.

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Study on the Front Detection Techniques by using Satellite Data (위성 자료를 이용한 전선 탐지 기법 연구)

  • Hwang, Do-Hyun;Bak, Su-Ho;Enkhjargal, Unuzaya;Jeong, Min-Ji;Kim, Na-Kyeong;Park, Mi-So;Kim, Bo-Ram;Yoon, Hong-Joo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.6
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    • pp.1201-1208
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    • 2020
  • A mass of seawater with similar properties in the ocean is called a water mass, and the front is a sea area where two masses of different properties meet. The gradient algorithm is a method of extracting where the sea water temperature pixel changes rapidly assuming that the slope is large, and the place with the large slope is assumed to be a front. This method is able to process large amounts of satellite data at once. Therefore, in this study, we tried to find the front lines in the sea area around the Korean Peninsula by using a gradient algorithm. The study data used gridded sea surface temperature satellite data. The resolution was 1/4°, and the monthly average data from January 1993 to December 2018 were used. There were major five fronts representatively, China Coastal Front, South Sea Coastal Front, Kuroshio Front/ Kuroshio Extension Front, Subpolar Front and the Subarctic Front. As a result of comparing the distribution of front by season, more types of front were distributed in winter and spring than in summer and autumn, and the distribution range was wider.

Bar Code Location Algorithm Using Pixel Gradient and Labeling (화소의 기울기와 레이블링을 이용한 효율적인 바코드 검출 알고리즘)

  • Kim, Seung-Jin;Jung, Yoon-Su;Kim, Bong-Seok;Won, Jong-Un;Won, Chul-Ho;Cho, Jin-Ho;Lee, Kuhn-Il
    • The KIPS Transactions:PartD
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    • v.10D no.7
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    • pp.1171-1176
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    • 2003
  • In this paper, we propose an effective bar code detection algorithm using the feature analysis and the labeling. After computing the direction of pixels using four line operators, we obtain the histogram about the direction of pixels by a block unit. We calculate the difference between the maximum value and the minimum value of the histogram and consider the block that have the largest difference value as the block of the bar code region. We get the line passing by the bar code region with the selected block but detect blocks of interest to get the more accurate line. The largest difference value is used to decide the threshold value to obtain the binary image. After obtaining a binary image, we do the labeling about the binary image. Therefore, we find blocks of interest in the bar code region. We calculate the gradient and the center of the bar code with blocks of interest, and then get the line passing by the bar code and detect the bar code. As we obtain the gray level of the line passing by the bar code, we grasp the information of the bar code.

Prediction of Postoperative Lung Function in Lung Cancer Patients Using Machine Learning Models

  • Oh Beom Kwon;Solji Han;Hwa Young Lee;Hye Seon Kang;Sung Kyoung Kim;Ju Sang Kim;Chan Kwon Park;Sang Haak Lee;Seung Joon Kim;Jin Woo Kim;Chang Dong Yeo
    • Tuberculosis and Respiratory Diseases
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    • v.86 no.3
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    • pp.203-215
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    • 2023
  • Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R2 and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R2 value was 0.27 and in set II, LightGBM was the best model with the highest R2 value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R2 value of 0.56 and the lowest MSE of 174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperative lung function.

A Study on the Preprocessing Method Using Construction of Watershed for Character Image segmentation

  • Nam Sang Yep;Choi Young Kyoo;Kwon Yun Jung;Lee Sung Chang
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.814-818
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    • 2004
  • Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

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Reduction of magnetic anomaly observations from helicopter surveys at varying elevations (고도가 변화하는 헬리콥터 탐사에서 얻어지는 자력이상의 변환)

  • Nakatsuka, Tadashi;Okuma, Shigeo
    • Geophysics and Geophysical Exploration
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    • v.9 no.1
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    • pp.121-128
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    • 2006
  • Magnetic survey flights by helicopters are usually parallel to the topographic surface, with a nominal clearance, but especially in high-resolution surveys the altitudes at which observations are made may be too variable to be regarded as a smooth surface. We have developed a reduction procedure for such data using the method of equivalent sources, where surrounding sources are included to control edge effects, and data from points distributed randomly in three dimensions are directly modelled. Although the problem is generally underdetermined, the method of conjugate gradients can be used to find a minimum-norm solution. There is freedom to select the harmonic function that relates the magnetic anomaly with the source. When the upward continuation function operator is selected, the equivalent source is the magnetic anomaly itself. If we select as source a distribution of magnetic dipoles in the direction of the ambient magnetic field, we can easily derive reduction-to-pole anomalies by rotating the direction of the magnetic dipoles to vertical.

A Noisy-Robust Approach for Facial Expression Recognition

  • Tong, Ying;Shen, Yuehong;Gao, Bin;Sun, Fenggang;Chen, Rui;Xu, Yefeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.4
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    • pp.2124-2148
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    • 2017
  • Accurate facial expression recognition (FER) requires reliable signal filtering and the effective feature extraction. Considering these requirements, this paper presents a novel approach for FER which is robust to noise. The main contributions of this work are: First, to preserve texture details in facial expression images and remove image noise, we improved the anisotropic diffusion filter by adjusting the diffusion coefficient according to two factors, namely, the gray value difference between the object and the background and the gradient magnitude of object. The improved filter can effectively distinguish facial muscle deformation and facial noise in face images. Second, to further improve robustness, we propose a new feature descriptor based on a combination of the Histogram of Oriented Gradients with the Canny operator (Canny-HOG) which can represent the precise deformation of eyes, eyebrows and lips for FER. Third, Canny-HOG's block and cell sizes are adjusted to reduce feature dimensionality and make the classifier less prone to overfitting. Our method was tested on images from the JAFFE and CK databases. Experimental results in L-O-Sam-O and L-O-Sub-O modes demonstrated the effectiveness of the proposed method. Meanwhile, the recognition rate of this method is not significantly affected in the presence of Gaussian noise and salt-and-pepper noise conditions.

Parametric Equation of Hough Transform for Log-Polar Image Representation (로그폴라 영상 표현을 위한 매개변수 방정식의 Hough 변환)

  • Choi, Il;Kim, Dong-su;Chien, Sung-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.4
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    • pp.455-461
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    • 2002
  • This paper presents a new parametric log line equation of polar form for Hough transform in log-polar plane, in which it can remove the well-known unboundedness problem of Hough parameters. Bolduc's method is used to generate a log-polar image dividing the fovea and periphery from a Cartesian image. Edges of the fovea and periphery are detected by using the Sobel mask and the proposed space-variant gradient mask, and are combined in the log-polar plane. The sampled points that might constitute a log line are quite sparse in a deep peripheral region due to severe under-sampling, which is an inherent property of LPM. To cope with such under-sampling, we determine the values of cumulative cells in Hough space by using the space-variant weighting. In our experiments, the proposed method demonstrates its validity of detecting not only the lines passing through both the fovea and periphery but also the lines in a deep periphery.

A Life Prediction of Insulation Degradation Using Complex Sensing System (복합 감지 시스템을 이용한 부분방전의 절연열화 수명추정)

  • Kim, S.H.;Kim, J.H.;Park, J.J.;Choi, J.K.;Yoon, H.J.;Lee, Y.S.
    • Proceedings of the KIEE Conference
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    • 1997.11a
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    • pp.348-350
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    • 1997
  • Because of internal voids ininsulators give rise to partial discharge(PD), which cause local breakdown and even entire insulation breakdown. Treeing due to PD is one of the main causes of breakdown of the insulating materials and reduction of the insulation life. Therefore the necessity for establishing a method to diagnose the aging of insulation materials and to predict the breakdown of insulation has become important. From this viewpoint, our studies diagnose insulation degradation using the method of computer sensing system, which has the advantages of PD and acoustic emission(AE) sensing system. To use advantages of these two methods can be used effectively to search for treeing location and PD in some materials. In analysis method of degradation. We analyzed the PD pulse and AE pulses by regression analysis, compared to these obtained the correlation coefficient and determination coefficient by T-distribution and saw that PD and AE pulses show a similar pattern on the whole. Finally using statically operator such as the center of gravity(G), the gradient of the discharge distribution(C), we have analyzed for the prediction of life which we can be obtained the time, occurred of many pulse of small discharge amplitude.

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Automatic Registration Between KOMPSAT-2 and TerraSAR-X Images (KOMPSAT-2 영상과 TerraSAR-X 영상 간 자동기하보정)

  • Han, You-Kyung;Byun, Young-Gi;Chae, Tae-Byeong;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.6
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    • pp.667-675
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    • 2011
  • In this paper, we propose an automatic image-to-image registration between high resolution multi-sensor images. To do this, TerraSAR-X image was shifted according to the initial translation differences of the x and y directions between images estimated using Mutual Information method. After that, the Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on the similarities of their locations and gradient orientations. For extracting large number of evenly distributed matching points, only one point within each regular grid constructed throughout the image was extracted to the final matching point pair. The model, which combined the piecewise linear function with the global affine transformation, was applied to increase the accuracy of the geometric correction, and the proposed method showed RMSE lower than 5m in all study sites.